Sr. Product Manager - Data Insights
New
H
HHAeXchangeHealth IT
Candidates located in the EST or CST time zones within the US only, EST or CSTFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years of experience in Product Management; 3+ years of experience in home health and/or home care solutions
- Required Skills
- AgileProduct ManagementSnowflakeJiraData analyticsConfluenceSaaS
Requirements
- 5+ years of experience in Product Management, preferably in the health IT vendor space.
- 3+ years of experience in home health and/or home care solutions.
- Bachelor's degree in Business, Computer Science, Engineering, or a related field.
- Deep understanding of SaaS business models, pricing, and customer management.
- Advanced product roadmap planning and prioritization skills.
- In-depth understanding of Agile Product Management and Development principles.
- Proficiency in customer journey mapping and VoC analysis.
- Ability to leverage data analytics to drive decisions.
- Working experience with Jira, Confluence, Aha!, or similar tools.
- Familiarity with API integration development, 3rd party support, web application framework, and database concepts.
- Experience working with overseas business analysts and engineering teams.
- Ability to travel 10-25%, including overnight travel.
Responsibilities
- Define and execute the product strategy for enterprise data insights leveraging Snowflake Cloud Data Platform.
- Partner with Data Engineering, Analytics, AI/ML, and business stakeholders to transform enterprise data into actionable insights.
- Identify opportunities to unlock business value through self-service analytics, ad hoc reporting, dashboards, and predictive models.
- Drive the product roadmap for enterprise reporting, data exploration, and advanced analytics capabilities.
- Evaluate and recommend modern BI, analytics, and AI tools to maximize business value.
- Identify opportunities to leverage machine learning and AI to automate insight generation and decision support.
- Define product requirements for predictive models supporting fraud detection, anomaly detection, forecasting, and operational optimization.
- Establish KPIs to measure the effectiveness, adoption, and business impact of data insight products.
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